| # Refund Request Classifier |
|
|
| This repository contains a logistic regression model developed to classify whether an email is a **response to a refund request** or **not**. |
|
|
| --- |
|
|
| ## 🚀 Quick Start |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| import joblib |
| |
| |
| # Load Model |
| model_path = hf_hub_download( |
| repo_id="Settlemate/refund-request-classifier", |
| filename="refund_request_classifier.pkl" |
| ) |
| |
| # Get Pipeline and Threshold |
| bundle = joblib.load(model_path) |
| pipeline = bundle["pipeline"] |
| threshold = bundle["threshold"] |
| |
| # Functions to use the classifier |
| def classify_refund_request(subject: str, body: str) -> bool: |
| text = f"{subject} {body}" |
| proba = pipeline.predict_proba([text])[0, 1] |
| return "refund-request" if proba >= threshold else "non-refund-request" |
| |
| |
| # Example usage |
| if __name__ == "__main__": |
| subject = "Order Order #210023: protocol REF-7701 assigned" |
| body = """<html><body><p>Protocol generated: REF-7701</p><p>Protocol REF-7701 has been issued for your refund request.</p><p>Status updates will be provided within 4 business days.</p><p>Check for updates by logging into our website.</p><p>Our customer care team is available for clarifications.</p><p>Sincerely,<br>QuickMart Support Team</p></body></html>""" |
| print(classify_refund_request(subject, body)) |
| ``` |
|
|
| --- |
|
|
| > **Note:** This model was trained using the <a href="https://huggingface.co/datasets/Settlemate/refund_response" target="_blank" rel="noopener noreferrer">dataset</a>, split into training, validation, and test sets. |
